6: Cartography I Flashcards
HISTORY OF CARTOGRAPHY
Maps have been produced for 1000s of years
Early civilisations:
Egypt (property maps)
Mesopotamia/Babylonia
China (6000 years ago)
Western society exploration:
Global maps became important for discovery, navigation, trade routes
Cartography evolution: Theoretical developments (flat earth) Technological changes (compass, printing press, GIS) Change in society's info needs (thematic mapping)
AWARENESS OF DESIGN
If we make a map attractive, people will want to read it
A map shouldn’t need explaining, it should just work
ART OR SCIENCE?
The role of cartography is to convey an idea to your readers and for them to interact with the map and feed it back to you
THEMATIC MAP CLASSIFICATION METHODS
Equal Interval
Quantiles
Mean-standard deviation
Natural breaks
PROPORTIONAL SYMBOL SCALING
also called ‘graduated symbol maps’
Represent numerical data associated with point locations, vary size of the symbol by the data
Area of point symbol is direct proportion to data
- true point data: measured at point locations
- conceptual point data: collected over areas but conceived as located points (centroid)
Thematic Maps / Statistical Maps
Map one or more variables (geographic attributes)
Types: Choropleth map Proportional symbol Isarithmic Dot Flow map
Choropleth map
Way of shading a map according to a variable to represent different magnitudes of an attribute
from Greek plethus = quantity, chorus = space
- attributes related to regions with standardised values (map a rate not just a number)
- represented by areal symbols (shading/colour)
Data Classification
Combining raw data into classes/groups, with each represented by unique symbol
Readers inability to discriminate among many different classes, max 5-7
Types of data classification (4)
Equal Interval
Quantiles
Mean-standard deviation
Natural breaks
Equal intervals
Each class occupies an equal interval along the number line
Each category has the same range (0-5, 5.1-10, 10.1-15, etc)
Quantiles
data are rank-ordered and equal numbers of observations are placed in each class
Recommended method to start with because it better reflects the distribution of the data relative to the number of observations
Quantiles is generic word for any numbers… quartile, quintile…
Mean-standard deviation
Classes formed by repeatedly adding/subtracting standard deviation from mean of the data
Emphasises highs and lows really well.
Cartograms
Distorted maps to give space to where the most observations of an attribute/data is
Density equalising projection
The size of the geographic areas is proportional to the amount of observations/data
Example:
Counties shown proportional to the number of people that live there
Tube map of London, gives more space for the city centre
Choropleth map pros/cons
Pro:
- easy to produce and read
- distribution patterns easy to recognise
Cons:
- badly misleading if inappropriately standarised
- cannot show variability within regions
- regions are often not appropriate for a theme
- most common pitfall: colours for quantities (red = high or danger)
Proportional symbol maps - what kind of symbols do we use?
Geometric symbols: common geometric shapes like circles or squares
Pictographic symbols: images, not as easy to read
